v2.0.0

Accuracy Defaults And Diagnostics

• CAMB now enables targeted accuracy improvements by default with the internal
  AccuracyTarget = 1. These changes are aimed at modern high-precision CMB,
  lensing, and matter-power use cases. Set AccuracyTarget = 0 in an .ini
  file, or camb.config.AccuracyTarget = 0 from Python, for behavior closer to
  the CAMB 1.x numerical-error profile.
• The new camb.check_accuracy module and camb check_accuracy command compare
  a requested calculation to a higher-accuracy reference, report CMB, lensing
  potential, matter-power, and derived-parameter differences, optionally make
  plots, and can search for minimal accuracy boosts.
• CAMBparams.set_for_lmax(..., lens_potential_accuracy=None) is now the public
  default. None selects an automatic high-accuracy lensing-potential/kmax
  setting, max(4, (lmax - 1500) / 500).
• Explicit lens_potential_accuracy values keep their old meaning. In
  particular, use lens_potential_accuracy=0 to reproduce the old low-k default
  behavior. set_params_cosmomc keeps its historical default
  lens_potential_accuracy=1; pass None there to opt into the new automatic
  rule.
• The automatic lens-potential rule is calibrated for lensed CMB spectra and
  lensing-potential stability at the relevant accuracy target. At high
  multipoles, remaining numerical errors in lensed spectra can be much smaller
  than the uncertainty from non-linear matter modelling.
• lens_output_margin is now a first-class Python and .ini parameter. It
  consistently controls how far above the requested lensed output range CAMB
  calculates internally, including the Fortran lensing convolution support.

Non-Flat Models And Hyperspherical Bessel Functions

• Non-flat scalar line-of-sight integration has been substantially refactored
  and sped up. The main changes are Numerov/source-grid integration, improved
  high-oscillation cutoffs, near-flat shifted-ν approximations, and direct Olver
  evaluation in high-substep ranges.
• Near-flat open and closed models can reuse flat Bessel table machinery where
  controlled local error estimates allow it. This improves speed near the flat
  limit while preserving continuity checks.
• The branch includes new hyperspherical Bessel implementations and validation
  paths: Olver-style approximations, small-chi/open-small-nu fallbacks, Airy
  utilities, and Python-accessible math utilities for testing.
• See detailed notes in hyperspherical_bessels.pdf and flat_bessel_approximations.pdf.

Lensing Calculations

• CAMB has a new optimized lensing method selector. It keeps the long-standing
  fast curved-sky method for ordinary runs and uses a full Gauss-Legendre
  curved-sky correlation method when AccurateBB=True.
• The direct curved-sky lensing implementation can also be selected explicitly,
  and Python calls such as get_lensed_cls_with_spectrum can temporarily
  override the lensing method for comparisons.
• The full-sky correlation code was optimized substantially, including cached
  Gauss-Legendre nodes/weights, inlined accumulation, recurrence-based factors,
  and faster Legendre tables exposed through camb.mathutils.
• Low-l EE tapering and high-L template extension behavior have been clarified
  and made more consistent between the Python and Fortran lensing paths.

Matter Power And Non-Linear Modelling

• Matter-power accuracy tuning was updated for massive neutrinos, photon and
  massless-neutrino hierarchy depths, and transfer-high-precision cases. The
  goal is better default agreement with boosted references without requiring
  broad global accuracy boosts.
• HMCode/Halofit evaluation was cleaned up and optimized. Cached HMCode
  redshift-local quantities give speedups of order 10-20% in the documented
  matter-power benchmarks, with only tiny changes from removing unintended
  single-precision round trips.
• CAMB now includes an SPkNonLinear model for the SP(k) baryon-suppression
  prescription, wrapping a base Halofit/HMCode model. It includes documented
  validity ranges, MCMC-friendly boundary behavior, and protections against
  double-counting baryonic feedback (thanks @jemme07, #194).
• New non-linear model hooks include ExternalNonLinearRatio for externally
  supplied non-linear ratios and SecondOrderPK for second-order perturbative
  matter-power ratios.

Recombination, Reionization, And Backgrounds

• The default BBN consistency relation now uses the September 2024 PRIMAT
  helium and deuterium table, replacing the 2021 PRIMAT table. For typical
  Planck-like models this lowers the default helium mass fraction by about
  2e-4, with sub-per-mille effects on fixed-parameter CMB spectra.
• RECFAST now uses a fast Rosenbrock integrator while stiff. The new
  path is tuned against high-accuracy internal references and scales with CAMB
  accuracy boosts. It is intended to improve the speed/accuracy tradeoff of the
  recombination background calculation.
• The default RECFAST approximation is now the recfast_cosmorec fit, including
  the helium-rate correction calibrated against direct CosmoRec histories.
  Planck-era RECFAST parameters remain available as recfast_planck and are
  explicitly used by Planck-specific compatibility inputs.
• The CosmoRec wrapper was updated for the newer CosmoRec vX interface and
  exposes the relevant CosmoRec controls through CAMB's recombination model.
• Reionization models now have an optional approximate heating switch that
  raises the baryon temperature and sound speed during reionization. It is off
  by default and is intended for order-of-magnitude low-redshift matter-power
  effects rather than precision thermal-history modelling.
• Thermal massive-neutrino background density and pressure now use direct smooth
  fits over the intermediate mass range, reducing setup/global state and modestly
  speeding repeated background evaluations.

Python Interface And New Capabilities

• A Python bispectrum wrapper is now available as camb.bispectrum. It runs the
  existing Fortran CMB-lensing or local-primordial bispectrum calculation using
  normal CAMBparams objects, writes large tables directly to files, and
  returns small Fisher summaries when the library is built with Fisher support.
• Documentation now includes pages for the bispectrum wrapper, SP(k), nonlinear
  models, check-accuracy workflow, and math utilities.
• CAMB now targets Python 3.11+ and uses the ruff/pre-commit toolchain for
  Python formatting and linting.
• The development tree includes updated devcontainer and CI configuration, but
  those changes are primarily for contributors rather than result-facing users.

Compatibility Notes

• Numerical outputs can change relative to CAMB 1.x because the v2 branch has a
  higher default accuracy target, different non-flat algorithms, updated
  lensing support, tuned matter-power accuracy settings, and RECFAST changes.
• For closer 1.x-style numerical behavior, start with AccuracyTarget = 0,
  explicit lens_potential_accuracy=0 in set_for_lmax, and fixed legacy
  matter-power settings where comparing against older runs.
• Users comparing old and new results should use camb check_accuracy and
  compare at fixed physical output ranges and k ranges. Avoid judging changes
  only from sparse grid-index differences, especially for matter power and
  high-l lensing.
• Some new options are deliberately off by default because they change the
  physical model rather than only the numerical method, for example reionization
  heating.